Data-independent mass spectrometry phenotyping of patient-derived melanoma cancer cell lines correlates with MEK inhibitor resistance independent of genotype and predicts poor patient outcome — ASN Events
  1. Schedule
  2. Symposium Eight: Disease Proteomics
  3. Data-independent mass spectrometry phenotyping of patient-derived melanoma cancer cell lines correlates with MEK inhibitor resistance independent of genotype and predicts poor patient outcome

Data-independent mass spectrometry phenotyping of patient-derived melanoma cancer cell lines correlates with MEK inhibitor resistance independent of genotype and predicts poor patient outcome (#034)

Christoph Krisp 1 , Robert Parker 1 , Dana Pascovici 1 , Nicholas Hayward 2 , Mark Molloy 1
  1. Australian Proteome Analysis Facility, Department of Chemistry & Biomolecular Sciences, Macquarie University, Sydney, New South Wales, Australia
  2. QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia

Melanoma accounts for only 5% of all skin cancer variants, but is the most common cause of skin cancer related deaths, and is responsible for killing more young (<40yrs) people than any other cancer. Despite initial success of drugs that target specific enzyme mutations, melanomas rapidly acquire drug resistance. To understand baseline protein processes in melanomas with different genetic mutational status, mitogen activated protein kinase (MAPK) pathway mutant melanomas were compared to MAPK wild type (wt) melanomas using data-independent mass spectrometry (SWATH-MS) profiling.

Ten patient-derived melanomas with known MAPK mutational status (3xBRAFmut, 3xNRASmut, 3xMAPKwt, 1xMEKmut) were cultured. Tryptic digests were submitted to LC-MS/MS on a TripleTOF 5600 MS (SCIEX) utilizing a multiphasic chip-based LC approach (reverse phase (RP), strong cation exchange, RP), for ion library generation to extract protein information from rapid 1h 1D RP SWATH-MS acquisitions per cell line. Presto Blue Assay was performed to assess ten-day cell viability in presence of the MEK inhibitor (MEKi) AZD6244.

This approach enabled comprehensive protein detection identifying 3200 proteins (10 cell lines; FDR<1%). Data extraction from SWATH-MS datasets revealed 2500 proteins quantifiable among these cell lines. Principal component analysis demonstrated segregation of melanomas based on sensitivity to MAPK inhibition (2 µM AZD6244), whereas genotype did not. In total, we show 57 proteins whose abundance correlate (r²>0.75) with MEKi cell viability, revealing changes in cell pigmentation, lipid metabolism, and in adherence and inter-cell communication. Kaplan – Meier survival analysis using post-surgery patient survival data demonstrated untreated patients with MEKi sensitive melanoma cells showed significantly (p=0.01) lower mortality rates than patients with MEKi resistant tumours (mean survival >7.5 years MEKi sensitive versus 1.7 years MEKi resistant).

Therefore, data-independent MS phenotyping of MAPK pathway mutant and wt melanoma cell lines demonstrated explicitly segregation of MEKi sensitive and resistant cell lines and is associated with patient outcome.